About

Sharan Yalburgi is a highly skilled Research Scientist at Julia Computing. With a Masters in Mathematics and a Bachelors in Computer Science from Birla Institute of Technology and Science, Pilani, he has a solid foundation in both fields. Sharan has over 2 years of relevant experience in machine learning and probabilistic programming languages (PPLs), and has previously worked as a Research Developer at the University of Cambridge, where he built a Gaussian Processes ecosystem in Julia under the mentorship of Dr Hong Ge and Will Tebbutt from the Machine Learning Group. Sharan has also worked as a Research Intern at the Massachusetts Institute of Technology, Department of Brain and Cognitive Sciences, under the guidance of Prof Vikash Mansinghka. During his internship, he gained valuable experience in research and development, which has helped him contribute significantly to the field of machine learning. Sharan's technical skills include expertise in research and development, as well as machine learning. He is highly proficient in programming languages such as Julia, Python, and C++, and has experience working with libraries such as TensorFlow, PyTorch, and Scikit-learn. Additionally, he is well-versed in probabilistic programming languages such as Turing.jl and Gen.jl. Sharan is an ambitious and driven individual who is passionate about contributing to the field of machine learning. He has a strong work ethic and is committed to delivering high-quality work. He is an excellent team player and has the ability to work collaboratively with colleagues from diverse backgrounds. In summary, Sharan Yalburgi is a skilled Research Scientist with a strong academic background and relevant experience in machine learning and probabilistic programming languages. He is an asset to any organization he works with and is committed to making a positive impact in the field of machine learning.